Categories:
TV search use case
Global use case developed by Aura Platform Team that allows users to search specific TV content in Aura
Introduction
The TV search use case is a global experience designed and developed by Aura Global Team that allows Telefónica customers to ask Aura for TV content using a vocal interface.
Find additional information in following the documents:
- Discover the TV search specifications and the particularities of the use case development.
- Learn how to configure the generic-dialog for TV search use case.
- Access to the TV search plugin.
- Discover which are the resources used by the TV search use case.
- Find out the NLP configuration for each OB for the TV search use case.
Specifications
Kernel API
In order to resolve the user’s search request, Aura uses Video Contents normalized Kernel API.
Request-response model
TV search use case is adapted to the new request-response normalized model v3.
Available channels
Once TV search v3 use case is fully normalized, it will be available for any channel that implements normalized v3 request-response model including TV related data.
Search features
Currently, the normalized TV search use case includes basic search features and smart answers for entertainment content:
- Search by title
- Search by genre (movie, series, documentaries, programs, short films and games)
- Search by subgenre (action, scare, love, etc)
- Search by actor or director
In addition to these search features, the use case includes a contingency or fallback search mode used in case the Video Contents API does not provide any answer to Aura request. The contingency or fallback search mode could be deactivated by configuration.
🆕 As a novelty in the current release, the use case is able to provide the users with smart answers features, meaning that the entities included in the user’s requests can be included in the answer.
Therefore, the answer could be of this type: “That’s what I’ve found about [$title, $participant, $genre, $subgenre]
For example:
- The user asks for a specific title: “Play a film starring Brad Pitt”
- In previous versions, Aura sends the content provided by the API as “That’s what I’ve found for you”
- Now, the entity can be included in the answer, giving the user a most personalized answer: “That’s what I’ve found about Brad Pitt”
Current limitations
Currently, the TV search use case does not include these features:
- Request for a specific season o episode of a TV Series.
- Search content from third-parties (content must belong to Aura’s catalog).
- Search including temporary entities or time intervals.
- Search sport content based on entities.
Use case development
The TV search use case development includes these components:
Understanding features
-
TV search use case intent:
intent.tv.search -
TV search use case entities:
| Entity | Example |
|---|---|
ent.audiovisual_film_title |
“Busca La princesa prometida” |
ent.audiovisual_documental_title |
“Busca ABBA Forever” |
ent.audiovisual_tvshow_title |
“Busca Late Motiv” |
ent.audiovisual_tvseries_title |
“Busca Hierro” |
ent.audiovisual_subgenre |
“Busca una comedia” |
ent.audiovisual_genre |
“Busca una película” |
ent.audiovisual_actor |
“Busca algo de Brad Pitt” |
ent.audiovisual_director |
“Busca algo de Almodóvar” |
⚠️ Other entities in the user’s request are not taken into account in the searching process.
In order to understand users’ requests (utterances), Aura is trained with:
- NLP expression to recognize the user’s utterance and detect her intention.
- TV catalog in order to understand TV content (titles, actors, director) in the user’s utterance and detect them as Aura entities.
- Other content like genre or subgenre.
Use case logic
Once Aura has recognized the user’s utterance based on NLP components, the use case should be resolved based on:
-
Aura Bot dialog:
TV search is built over the generic-dialog-v3.
- Check the section Configuration of the generic-dialog for TV search use case in order to know the required configuration for the TV search experience.
-
CLF Plugin:
Complex Logic Framework is used for the recognition of the user’s request.
- Check here the TV search plugin.